Data Governance, a pursuit to ensure data is fit for its purpose; behaviours and cultures need to adapt to achieve Data Governance, however, there are many legitimate reasons why this can be challenging to accomplish.
Each organisations’ Data Governance journey will differ due to individual and unique business strategies which influence areas of focus and priorities. An ability to create a bespoke Data Governance programme should not be misconstrued as meaning Data Governance principles are optional. Push back and discussion is a good way to build sponsorship and support, however, it needs to be proportionate. A crippling level of reticence will prevent any real positives from being realised. Care should be taken to adopt and adapt rather than reject and remove the foundational aspects needed to build a successful Data Governance programme. Finding middle ground without the loss of core ideals is a proposed and desirable outcome. Employing a Data Governance practitioner does not (unfortunately) automatically result in the acceptance of Data Governance. New propositions will often create debate throughout the first year of a programme. During this article I will discuss commonly experienced challenges in the hope of helping its engagement.
Governance overload?
Most organisations will already be performing Data Governance to some degree, formal Data Governance allows a standard approach and ideally removes ad hoc non-committal from an organisation. Most are familiar with established Compliance initiatives created to uphold approved ways of working. The introduction of Data Governance on top of established Compliance teams can create governance fatigue and internal friction. While a programme finds its feet there can be some duplication of effort between existing and new proposed ways of working. It is a difficult balance to reach; if core principles of Data Governance are rejected in lieu of a well-known and understood compliance strategy, the stronger, more established offering can over power a new Data Governance programme before it has even started. It is human nature to fear or avoid the unknown especially when taken outside of a comfort zone; Signpost a governance programme as a supporter of successful and positive ways of working, this can help to dispel the myth its adoption requires a complete overhaul (in most instances). The nuances between compliance led teams can be difficult to comprehend if you do not work within or closely to them. It wouldn’t be unusual to view them as one in the same, especially if they contain the word data in their titles. Top tip make it easy for your organisation to understand the differences and delineation of responsibilities, don’t assume it automatically make sense.
What’s in a name?
Unless Data Governance is viewed as an enabler, with the potential for flexible, proportionate and appropriate controls, it is unlikely to be accepted. It can be tempting to start big if there is pressure to provide big wins to garner support. Most governance programmes take time. A focus on organisation led priorities can help, however, they need to be realistic. Success may require a complete rebrand. “Data Excellence”, “Data Monetisation”, or “Data Enablement” to name a few new names which are emerging to address the lack of support a governance led initiative can receive. A quick google search will produce a number of articles which discuss this topic at length so I won’t go into too much detail here. A concern with this is a different name can change the purpose. To govern something is not the same as data excellence, monetisation or enablement. New descriptors fail to cover nonspecific outcomes of governance. What if your data isn’t excellent and it doesn’t need to be. By kowtowing to negative word associations it may solve one conundrum while creating another.
Great idea in theory!
Very little happens without the involvement of data, ergo it is significant and needs to be looked after. Most will be comfortable with this conclusion, where the fun begins is trying to decide who is responsible for bringing a Data Governance programme to life. Data Governance requires the adoption of key roles which create responsibility and accountability for data. How these roles are adopted will depend on which operating model is chosen. The size of an organisation also influences which model makes the most sense.
Below are examples of potential operating models along with a very basic description.
- De-Centralised – data is looked after in siloes with individual business units having full autonomy (potentially very similar to organisations without a formal governance processes)
- Federated – responsibility for adopting and enacting belongs to individual business units, with a small data governance team to provide guidance and support
- Hybrid – Business units manage data with support from a larger data governance team who own data operations and data governance as a whole
- Fully Centralised – a central data team owns all domains of data, with a singular point for decision making and controls
There are pros and cons for all iterations. I prefer a Federated approach as it leans itself to growing knowledge and continuous improvement organisation wide.
I’m too busy!
It’s often the busiest teams who have the most need for Data Governance. Governing data might be a simple idea, but it can be very difficult to bring to life. It relies heavily on people. It should be a safe assumption a governance programme has the potential to succeed. A governance practitioner can only do so much. There needs to be a willingness at all levels to adopt new ways of working.
Carrot or the stick?
Unless data is adopted into traditional notions of accountability a Governance programme will remain optional with little to no repercussions felt by those who legitimately or illegitimately prioritise other work commitments. Aside from governance weary colleagues who actively avoid, disparage or dismiss Data Governance, supporters need to be allowed to prioritise data, giving colleagues’ bandwidth, budget, and support is essential. A Peter Drucker oft quoted observation “Culture eats strategy for breakfast” couldn’t be truer for most Data Governance programmes.